Research on Fault Diagnosis and Forecast System of Forest Harvester Based on CAN-bus Information
The fault diagnosis of forest harvester is updating with the application of CAN bus technology. Aiming at the CAN technology which was utilized on forest harvester currently, the complexity of the fault information and the difficulty of diagnosis, an USBCAN intelligent interface card was designed in this paper. Based on the interface card, the software of Microsoft Visual C++6.0 is utilized to build the fault diagnosis system with BP neural network and Kalman filter. The fault diagnosis and forecast to the main systems of forest harvester were released online after incepting, filtering and removing the noise of the signal from the CAN bus. As the experiments show that Kalman filtering plays good on removal of noise from the complex fault signal, and the BP neural network trainings of the systems are effective to implement non-linear mapping from the fault phenomenon to the fault position of forest harvester.
Fault Diagnosis of forest engineering equipment bus of Controller Area of Network Kalman filtering Back-propagation Neural Network
Wang Dian Liu Jinhao Zhang Bo
College of Technology Beijing Forestry University Beijing, China Hei Long Jiang Chen Neng Investment Management Co.Ltd Harbin, China
国际会议
成都
英文
105-108
2010-06-12（万方平台首次上网日期，不代表论文的发表时间）